In the past years, promotions have been continually growing in sales and consumer behavior influence. However, the demand variability imposed promotes stress in the whole supply chain, especially concerning the expected demand of each product – promotional forecast.
Being able to accurately predict promotional demand involves many decisions where typically analytical models delivered superior results and unbiased insights.
Yet, there are several challenges placed every time that deserves to be considered regarding this process.
Although promotions face an increasing impact on the consumer, one pivotal fact is the need to have products available on the shelf to the end customer. If too much product is placed for a promotion it could result in shrinkage or negative margins due to product natural life-cycle. Subsequently, this might induce an over-dimensional operation with higher risk and capital invested.
As opposite, an out-of-stock situation will impact customer satisfaction and loyalty. For manufacturers, out-of-stock could be even more damaging and lead to a competitive disadvantage with a loss of brand equity and loyalty. As promotional impact increases the more imperative will be to have a balanced situation and by using a more rigorous forecast less stock will be needed to fulfill possible forecast-demand deviation and, consequently, decreasing risk.
Predicting promotions is considerably more complex than predicting non-promoted products. The number of factors influencing demand change within promotions and, for similar promotional conditions, the data available is considerably less or non-existent. Marketing campaigns, price, store display, geographic location, brand, gifts, and many other features consistently impact how clients react to promotions.
Nowadays, there are several models and methodologies to tackle this problem, however, it is necessary to have the analytical expertise to parametrize and understand the black box that not always deliver the expected outcome.
The probability of ending up at an overfitted situation with meaningless results is higher, but when correctly applied is possible to take advantages increasing forecast accuracy and, especially, promotional knowledge.
With an advanced understanding of each feature impact, promotional plans have more information to meet the expected results and be in line with organization strategy.
New products introduction and promotional assortment add even more complexity into this process. With an increasing product diversification, the differences with similar products are narrower and, in many cases, irrelevant for client requirements and satisfaction. This creates an intense network of product interactions where one promotion has an impact on others promoted and non-promoted products.
The introduction of new products enhances the density of the problem by requiring a forecast without historical data to support the analysis. On this subject, product attributes and similar products have an important role in order to prepare and get a sustainable forecast. By looking for attributes instead of individual products it is possible to get close to future demand and products interactions – leveraging the available information.
Promotional forecasting is a process ready for improvement and there are plenty of options to achieve it.
With good processes and technology, organizations can continue to exploit the benefits of promotion without tarnishing it by using inaccurate forecasts.
This consequently leads to better promotions plans with better information, which helps further forecast to be more accurate. What follows is a significant cost reduction and a synchronized supply chain.
Besides, having a good methodology could be the core point to leverage the business and take advantage over the competition.